IoT-driven reflectance-based multimode colorimeter for real-time monitoring of crystallization process: A study on oleogels

Abstract

This study explores the application of an Internet of Things (IoT)-driven reflectance-based multimode colorimeter for real-time monitoring of the crystallization process in oleogels-a novel class of structured lipids gaining popularity in the food industries. These structured lipids offer a healthier alternative to solid fats, but their texture and stability rely on precise control of crystallization process. Traditional monitoring methods, such as atomic force microscopy and spectroscopy, are expensive and lack real-time capabilities. The proposed device can operate in two modes: quality testing and process monitoring modes. In the quality testing mode, the device exhibits superior color accuracy compared to a commercial device, making it a reliable tool for color assessment (ΔE values < 10). In the process monitoring mode, the device effectively tracks crystallization kinetics at different incubation temperatures (5 °C, 15 °C, and 25 °C), revealing the impact of sunflower lecithin on primary and secondary crystallization phases. Further, the temperature vs. L* data offers more profound insights into oleogel crystallization, validated by Differential Scanning Calorimetry (DSC) analysis. Additionally, the device's performance was tested by monitoring the crystallization process of butter. The results obtained from the device closely matched the DSC findings, which enhanced our understanding of the crystallization processes in butter. This showcases the potential of the device for analyzing food samples.